Kim Smuga-Otto

13.8k total citations · 2 hit papers
8 papers, 10.1k citations indexed

About

Kim Smuga-Otto is a scholar working on Molecular Biology, Cell Biology and Genetics. According to data from OpenAlex, Kim Smuga-Otto has authored 8 papers receiving a total of 10.1k indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Molecular Biology, 3 papers in Cell Biology and 1 paper in Genetics. Recurrent topics in Kim Smuga-Otto's work include Pluripotent Stem Cells Research (7 papers), CRISPR and Genetic Engineering (7 papers) and Zebrafish Biomedical Research Applications (3 papers). Kim Smuga-Otto is often cited by papers focused on Pluripotent Stem Cells Research (7 papers), CRISPR and Genetic Engineering (7 papers) and Zebrafish Biomedical Research Applications (3 papers). Kim Smuga-Otto collaborates with scholars based in United States. Kim Smuga-Otto's co-authors include Junying Yu, Igor I. Slukvin, James A. Thomson, Shulan Tian, Ron Stewart, Maxim A. Vodyanik, Jessica Antosiewicz‐Bourget, Jeff Nie, Guðrún A. Jónsdóttir and Victor Ruotti and has published in prestigious journals such as Science, Proceedings of the National Academy of Sciences and Biochemical and Biophysical Research Communications.

In The Last Decade

Kim Smuga-Otto

8 papers receiving 9.8k citations

Hit Papers

Induced Pluripotent Stem Cell Lines Derived from Human So... 2007 2026 2013 2019 2007 2009 2.5k 5.0k 7.5k
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Induced Pluripotent Stem Cell Lines Derived from Human Somatic Cells
    2007 7.5k citations Junying Yu, Maxim A. Vodyanik et al. Science profile →
  2. Human Induced Pluripotent Stem Cells Free of Vector and Transgene Sequences
    2009 1.7k citations Junying Yu, Kejin Hu et al. Science profile →

Peers

Kim Smuga-Otto
Maxim A. Vodyanik United States
Jeff Nie United States
Shulan Tian United States
Guðrún A. Jónsdóttir United States
In-Hyun Park United States
Igor I. Slukvin United States
Vivienne S. Marshall United States
Michelle Waknitz United States
Andrew G. Elefanty Australia
Matthias Stadtfeld United States
Maxim A. Vodyanik United States
Kim Smuga-Otto
Citations per year, relative to Kim Smuga-Otto Kim Smuga-Otto (= 1×) peers Maxim A. Vodyanik

Countries citing papers authored by Kim Smuga-Otto

Since Specialization
Citations

This map shows the geographic impact of Kim Smuga-Otto's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Kim Smuga-Otto with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kim Smuga-Otto more than expected).

Fields of papers citing papers by Kim Smuga-Otto

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kim Smuga-Otto. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Kim Smuga-Otto. The network helps show where Kim Smuga-Otto may publish in the future.

Co-authorship network of co-authors of Kim Smuga-Otto

This figure shows the co-authorship network connecting the top 25 collaborators of Kim Smuga-Otto. A scholar is included among the top collaborators of Kim Smuga-Otto based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Kim Smuga-Otto. Kim Smuga-Otto is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

8 of 8 papers shown
1.
Vermilyea, Scott, Michaël Meyer, Kim Smuga-Otto, et al.. (2017). Induced Pluripotent Stem Cell-Derived Dopaminergic Neurons from Adult Common Marmoset Fibroblasts. Stem Cells and Development. 26(17). 1225–1235. 25 indexed citations
2.
Smuga-Otto, Kim. (2017). Zebrafish assay forges new approach to drug discovery. Proceedings of the National Academy of Sciences. 115(21). 5306–5308. 4 indexed citations
3.
Yu, Junying, Kejin Hu, Kim Smuga-Otto, et al.. (2009). Human Induced Pluripotent Stem Cells Free of Vector and Transgene Sequences. Science. 324(5928). 797–801. 1718 indexed citations breakdown →
4.
Yu, Junying, Kim Smuga-Otto, Giorgia Salvagiotto, et al.. (2009). Hematopoietic and Endothelial Differentiation of Human Induced Pluripotent Stem Cells. Stem Cells. 27(3). 559–567. 369 indexed citations
5.
Choi, Kyung-Dal, Junying Yu, Kim Smuga-Otto, et al.. (2009). Hematopoietic and endothelial differentiation of human induced pluripotent stem cells. Stem Cells. 27(3). 559–567. 161 indexed citations
6.
Yu, Junying, Maxim A. Vodyanik, Kim Smuga-Otto, et al.. (2008). Induced Pluripotent Stem Cell Lines Derived From Human Somatic Cells. Obstetrical & Gynecological Survey. 63(3). 154–155. 300 indexed citations
7.
Yu, Junying, Maxim A. Vodyanik, Kim Smuga-Otto, et al.. (2007). Induced Pluripotent Stem Cell Lines Derived from Human Somatic Cells. Science. 318(5858). 1917–1920. 7504 indexed citations breakdown →
8.
Kameda, Takashi, Kim Smuga-Otto, & James A. Thomson. (2006). A severe de novo methylation of episomal vectors by human ES cells. Biochemical and Biophysical Research Communications. 349(4). 1269–1277. 18 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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